-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\knm4642\Dropbox\Nha Meo Heo Beo\_JMP\WORKING FOLDER\Table A12_Effect by background and experience.log
  log type:  text
 opened on:  18 Feb 2026, 23:52:50

. 
. //PREPARE DATA
. use "Baseline CEO firm year sample.dta", clear

. * construct additional variables
. gen postgradnonMBA = (education == 3 & MBA == 0) | education == 4

. gen postgrad = education == 3 | education == 4

. gen hasPhD = education == 4

. foreach var of varlist postgrad postgradnonMBA postgrad hasPhD {
  2.         replace `var' = . if education == .
  3. }
(6,457 real changes made, 6,457 to missing)
(6,457 real changes made, 6,457 to missing)
(0 real changes made)
(6,457 real changes made, 6,457 to missing)

. gen hasRDexp = preCEO_resdir == 1 | preCEO_techdir == 1

. gen above3yrinco = yrinco > 3

. * set globals
. global firm = "firmage firmage2"

. global sample = "year < 2012 & !nonUS"

. global cluster = "mainethcode"

. 
. //PREPARE TABLE
. eststo clear

. global ceo = "gender age age2 yrinco"

. cap drop D

. gen D = postgrad
(6,457 missing values generated)

. eststo col1: /// graduate degree
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(   9,     37) =      25.58
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0021
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0762685   .0168974     4.51   0.000     .0420312    .1105059
          1  |   .0535779   .0239903     2.23   0.032     .0049689    .1021869
             |
           D |   .1408503   .1466221     0.96   0.343    -.1562344     .437935
     firmage |  -.0111438   .0018596    -5.99   0.000    -.0149117   -.0073759
    firmage2 |   .0001166   .0000496     2.35   0.024     .0000161    .0002172
      gender |  -.0115113   .0329061    -0.35   0.728    -.0781855    .0551628
         age |  -.0010934   .0103849    -0.11   0.917    -.0221351    .0199483
        age2 |  -7.21e-06   .0000855    -0.08   0.933    -.0001804     .000166
      yrinco |   .0041041   .0005851     7.01   0.000     .0029186    .0052896
       _cons |    .782465   .2978959     2.63   0.012     .1788706     1.38606
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Graduate"

added macro:
               e(Dvar) : "Graduate"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col1, add(nofirms r(ndistinct))  
(e(nofirms) = 3598 added)

. replace D = hasPhD
(21,614 real changes made)

. eststo col2: /// doctorate degree
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(   9,     37) =      30.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0729132   .0143854     5.07   0.000     .0437655    .1020609
          1  |   .0084812   .0592151     0.14   0.887    -.1114999    .1284624
             |
           D |   .3599566   .3073663     1.17   0.249    -.2628266    .9827399
     firmage |  -.0110322   .0019313    -5.71   0.000    -.0149454    -.007119
    firmage2 |   .0001137   .0000495     2.30   0.027     .0000134    .0002141
      gender |  -.0141015   .0329093    -0.43   0.671    -.0807821    .0525791
         age |  -.0009457   .0104895    -0.09   0.929    -.0221994    .0203079
        age2 |  -9.15e-06   .0000863    -0.11   0.916    -.0001841    .0001657
      yrinco |   .0039904   .0005579     7.15   0.000     .0028601    .0051208
       _cons |   .8104158   .3022514     2.68   0.011     .1979963    1.422835
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Doctorate"

added macro:
               e(Dvar) : "Doctorate"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col2, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = postgradnonMBA
(5,406 real changes made)

. eststo col3: /// non-MBA graduate degree
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(   9,     37) =      21.75
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0023
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0933001   .0217546     4.29   0.000      .049221    .1373791
          1  |  -.0082729   .0361865    -0.23   0.820    -.0815937     .065048
             |
           D |   .5370478   .2486205     2.16   0.037     .0332948    1.040801
     firmage |  -.0113395   .0019382    -5.85   0.000    -.0152667   -.0074124
    firmage2 |   .0001147   .0000501     2.29   0.028     .0000132    .0002161
      gender |  -.0138863   .0323018    -0.43   0.670    -.0793359    .0515634
         age |  -.0012706   .0104749    -0.12   0.904    -.0224948    .0199536
        age2 |  -6.60e-06    .000086    -0.08   0.939    -.0001808    .0001676
      yrinco |    .004041   .0005834     6.93   0.000     .0028589    .0052232
       _cons |   .7201336   .2847976     2.53   0.016     .1430788    1.297188
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Non-MBA grad"

added macro:
               e(Dvar) : "Non-MBA grad"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col3, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. global ceo = "gender age age2 yrinco i.education"

. replace D = hasRDexp
(20,601 real changes made)

. eststo col4: /// prior R&D experience
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      42.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0635729   .0151284     4.20   0.000     .0329198     .094226
          1  |   .0005562   .1331137     0.00   0.997    -.2691578    .2702703
             |
           D |   .2979521   .6115311     0.49   0.629    -.9411276    1.537032
     firmage |  -.0110074    .001892    -5.82   0.000    -.0148409   -.0071739
    firmage2 |   .0001159   .0000491     2.36   0.024     .0000164    .0002154
      gender |  -.0124502   .0337422    -0.37   0.714    -.0808185     .055918
         age |  -.0013066   .0104545    -0.12   0.901    -.0224893    .0198762
        age2 |  -5.71e-06   .0000854    -0.07   0.947    -.0001787    .0001672
      yrinco |   .0041069   .0006488     6.33   0.000     .0027924    .0054214
             |
   education |
          2  |   .0434882   .0489096     0.89   0.380    -.0556121    .1425885
          3  |   .0601535   .0340231     1.77   0.085     -.008784    .1290909
          4  |   .0851727   .0426696     2.00   0.053    -.0012841    .1716296
             |
       _cons |   .8121786   .3046933     2.67   0.011     .1948113    1.429546
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "R\&D exp"

added macro:
               e(Dvar) : "R\&D exp"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col4, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. global ceo = "gender age age2 i.education"

. replace D = above3yrinco
(44,670 real changes made)

. eststo col5: /// more than 3 years in firm
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  11,     37) =      20.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8874
                                                  Within R-sq.    =     0.0013
Number of clusters (mainethcode) =         38     Root MSE        =     0.5429

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0760444   .0279047     2.73   0.010      .019504    .1325848
          1  |    .052522   .0232862     2.26   0.030     .0053396    .0997044
             |
           D |   .1402259   .1907154     0.74   0.467    -.2462002     .526652
     firmage |  -.0089489   .0016682    -5.36   0.000     -.012329   -.0055688
    firmage2 |   .0000994   .0000451     2.20   0.034     7.96e-06    .0001908
      gender |  -.0148585   .0343966    -0.43   0.668    -.0845527    .0548357
         age |  -.0042024   .0102199    -0.41   0.683    -.0249099     .016505
        age2 |   .0000346   .0000835     0.41   0.681    -.0001345    .0002038
             |
   education |
          2  |    .033927   .0478511     0.71   0.483    -.0630285    .1308825
          3  |   .0473525   .0321659     1.47   0.149    -.0178218    .1125269
          4  |   .0760045    .040262     1.89   0.067     -.005574    .1575829
             |
       _cons |   .8021368    .330419     2.43   0.020     .1326443    1.471629
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       ">3 yrs in firm"

added macro:
               e(Dvar) : ">3 yrs in firm"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col5, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. global ceo = "gender age age2 yrinco i.education"

. replace D = firstgen | nonUSUKedu
(43,302 real changes made)

. eststo col6: /// born or educated abroad
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      15.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0026
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0588936   .0197989     2.97   0.005     .0187772      .09901
          1  |   .1154804   .0642406     1.80   0.080    -.0146833    .2456442
             |
           D |  -.1986203   .3673142    -0.54   0.592    -.9428695     .545629
     firmage |  -.0109566   .0018651    -5.87   0.000    -.0147356   -.0071775
    firmage2 |   .0001161   .0000492     2.36   0.024     .0000164    .0002159
      gender |    -.00997    .033395    -0.30   0.767    -.0776347    .0576947
         age |   -.001197   .0102187    -0.12   0.907    -.0219022    .0195081
        age2 |  -6.83e-06   .0000836    -0.08   0.935    -.0001763    .0001626
      yrinco |    .004086   .0005681     7.19   0.000     .0029349    .0052371
             |
   education |
          2  |    .044987   .0476338     0.94   0.351    -.0515282    .1415022
          3  |   .0599782   .0323444     1.85   0.072    -.0055578    .1255143
          4  |   .0810759   .0423416     1.91   0.063    -.0047164    .1668682
             |
       _cons |   .8247418    .289963     2.84   0.007     .2372209    1.412263
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Born/edu abroad"

added macro:
               e(Dvar) : "Born/edu abroad"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col6, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = firstgen
(4,123 real changes made)

. eststo col7: /// born abroad
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      18.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0026
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0563453   .0188047     3.00   0.005     .0182433    .0944473
          1  |   .2993526   .0818225     3.66   0.001     .1335645    .4651407
             |
           D |  -1.035664   .4483461    -2.31   0.027      -1.9441   -.1272288
     firmage |  -.0109904   .0019418    -5.66   0.000    -.0149248   -.0070559
    firmage2 |   .0001173   .0000495     2.37   0.023     .0000169    .0002177
      gender |  -.0121233   .0334059    -0.36   0.719    -.0798101    .0555635
         age |  -.0008853   .0102221    -0.09   0.931    -.0215973    .0198267
        age2 |  -.0000105   .0000836    -0.13   0.901    -.0001798    .0001589
      yrinco |    .004132   .0005837     7.08   0.000     .0029494    .0053147
             |
   education |
          2  |   .0456167   .0457926     1.00   0.326    -.0471679    .1384014
          3  |   .0625828   .0311791     2.01   0.052     -.000592    .1257576
          4  |   .0832472   .0402327     2.07   0.046     .0017279    .1647664
             |
       _cons |   .8352572   .2904295     2.88   0.007     .2467912    1.423723
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Born abroad"

added macro:
               e(Dvar) : "Born abroad"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col7, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = sameethnames
(10,831 real changes made, 6,909 to missing)

. eststo col8: /// same-ethnicity first name
>         reghdfe ash_f1allpat c.trust_sd#i.D D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     28,035
Absorbing 2 HDFE groups                           F(  12,     37) =      98.06
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9037
                                                  Adj R-squared   =     0.8899
                                                  Within R-sq.    =     0.0021
Number of clusters (mainethcode) =         38     Root MSE        =     0.5404

                           (Std. err. adjusted for 38 clusters in mainethcode)
------------------------------------------------------------------------------
             |               Robust
ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
D#c.trust_sd |
          0  |   .0580007   .0179005     3.24   0.003     .0217309    .0942705
          1  |   .1434684   .0504826     2.84   0.007      .041181    .2457558
             |
           D |  -.3857387   .2826082    -1.36   0.181    -.9583573    .1868799
     firmage |  -.0095657   .0015761    -6.07   0.000    -.0127591   -.0063723
    firmage2 |   .0000926   .0000454     2.04   0.048     7.15e-07    .0001845
      gender |  -.0247958     .04116    -0.60   0.551     -.108194    .0586023
         age |  -.0051534   .0108498    -0.47   0.638    -.0271371    .0168303
        age2 |   .0000284   .0000893     0.32   0.752    -.0001524    .0002093
      yrinco |   .0036582   .0006244     5.86   0.000     .0023931    .0049234
             |
   education |
          2  |   .0284186   .0510076     0.56   0.581    -.0749327    .1317699
          3  |   .0338993   .0356944     0.95   0.348    -.0384245     .106223
          4  |    .063694   .0462486     1.38   0.177    -.0300146    .1574026
             |
       _cons |   .9747945   .3228819     3.02   0.005     .3205735    1.629015
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3495           0        3495     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Same-eth names"

added macro:
               e(Dvar) : "Same-eth names"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      28035       3495

.                 eststo col8, add(nofirms r(ndistinct))
(e(nofirms) = 3495 added)

.                 
. esttab /*using "Table A12_Effect by background and experience.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         nomtitle collabels(none) label varwidth(23) modelwidth(13) ///
>         mgroups("arsinh(Future patent applications)", pattern(1 0 0 0 0 0 0 0) ///
>                 prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(0.D#c.trust_sd 1.D#c.trust_sd) order(0.D#c.trust_sd 1.D#c.trust_sd) ///
>         coeflab(0.D#c.trust_sd "A: Trust $\times$ D = 0" ///
>                         1.D#c.trust_sd "B: Trust $\times$ D = 1") ///
>         stats(Dvar FE controls N nofirms, fmt(%9.0fc %9.0fc) ///
>                 lab("CEO's background" "Firm \& Year FEs" "Baseline controls" "Observations" "Firms"))

---------------------------------------------------------------------------------------------------------------------------------------------------------------
                        \multicolumn{8}{c}{arsinh(Future patent applications)}                                                                                 
                                  (1)              (2)              (3)              (4)              (5)              (6)              (7)              (8)   
---------------------------------------------------------------------------------------------------------------------------------------------------------------
A: Trust $\times$ D = 0         0.076***         0.073***         0.093***         0.064***         0.076***         0.059***         0.056***         0.058***
                              (0.017)          (0.014)          (0.022)          (0.015)          (0.028)          (0.020)          (0.019)          (0.018)   
B: Trust $\times$ D = 1         0.054**          0.008           -0.008            0.001            0.053**          0.115*           0.299***         0.143***
                              (0.024)          (0.059)          (0.036)          (0.133)          (0.023)          (0.064)          (0.082)          (0.050)   
---------------------------------------------------------------------------------------------------------------------------------------------------------------
CEO's background             Graduate        Doctorate     Non-MBA grad         R\&D exp    >3 yrs in firm    Born/edu abroad      Born abroad    Same-eth names   
Firm \& Year FEs                    X                X                X                X                X                X                X                X   
Baseline controls                   X                X                X                X                X                X                X                X   
Observations                   29,384           29,384           29,384           29,384           29,384           29,384           29,384           28,035   
Firms                           3,598            3,598            3,598            3,598            3,598            3,598            3,598            3,495   
---------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. 
. //PRINT DIFFERENCES
. eststo clear

. global ceo = "gender age age2 yrinco"

. cap drop D

. gen D = postgrad
(6,457 missing values generated)

. eststo col1: /// graduate degree
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(   9,     37) =      25.58
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0021
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0762685   .0168974     4.51   0.000     .0420312    .1105059
             D |   .1408503   .1466221     0.96   0.343    -.1562344     .437935
               |
c.trust_sd#c.D |  -.0226906   .0285819    -0.79   0.432    -.0806032    .0352219
               |
       firmage |  -.0111438   .0018596    -5.99   0.000    -.0149117   -.0073759
      firmage2 |   .0001166   .0000496     2.35   0.024     .0000161    .0002172
        gender |  -.0115113   .0329061    -0.35   0.728    -.0781855    .0551628
           age |  -.0010934   .0103849    -0.11   0.917    -.0221351    .0199483
          age2 |  -7.21e-06   .0000855    -0.08   0.933    -.0001804     .000166
        yrinco |   .0041041   .0005851     7.01   0.000     .0029186    .0052896
         _cons |    .782465   .2978959     2.63   0.012     .1788706     1.38606
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Graduate"

added macro:
               e(Dvar) : "Graduate"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col1, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = hasPhD
(21,614 real changes made)

. eststo col2: /// doctorate degree
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(   9,     37) =      30.35
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0729132   .0143854     5.07   0.000     .0437655    .1020609
             D |   .3599566   .3073663     1.17   0.249    -.2628266    .9827399
               |
c.trust_sd#c.D |   -.064432   .0602705    -1.07   0.292    -.1865515    .0576876
               |
       firmage |  -.0110322   .0019313    -5.71   0.000    -.0149454    -.007119
      firmage2 |   .0001137   .0000495     2.30   0.027     .0000134    .0002141
        gender |  -.0141015   .0329093    -0.43   0.671    -.0807821    .0525791
           age |  -.0009457   .0104895    -0.09   0.929    -.0221994    .0203079
          age2 |  -9.15e-06   .0000863    -0.11   0.916    -.0001841    .0001657
        yrinco |   .0039904   .0005579     7.15   0.000     .0028601    .0051208
         _cons |   .8104158   .3022514     2.68   0.011     .1979963    1.422835
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Doctorate"

added macro:
               e(Dvar) : "Doctorate"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col2, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = postgradnonMBA
(5,406 real changes made)

. eststo col3: /// non-MBA graduate degree
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(   9,     37) =      21.75
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0023
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0933001   .0217546     4.29   0.000      .049221    .1373791
             D |   .5370478   .2486205     2.16   0.037     .0332948    1.040801
               |
c.trust_sd#c.D |  -.1015729   .0473684    -2.14   0.039    -.1975504   -.0055954
               |
       firmage |  -.0113395   .0019382    -5.85   0.000    -.0152667   -.0074124
      firmage2 |   .0001147   .0000501     2.29   0.028     .0000132    .0002161
        gender |  -.0138863   .0323018    -0.43   0.670    -.0793359    .0515634
           age |  -.0012706   .0104749    -0.12   0.904    -.0224948    .0199536
          age2 |  -6.60e-06    .000086    -0.08   0.939    -.0001808    .0001676
        yrinco |    .004041   .0005834     6.93   0.000     .0028589    .0052232
         _cons |   .7201336   .2847976     2.53   0.016     .1430788    1.297188
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Non-MBA grad"

added macro:
               e(Dvar) : "Non-MBA grad"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col3, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. global ceo = "gender age age2 yrinco i.education"

. replace D = hasRDexp
(20,601 real changes made)

. eststo col4: /// prior R&D experience
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      42.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0022
Number of clusters (mainethcode) =         38     Root MSE        =     0.5427

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0635729   .0151284     4.20   0.000     .0329198     .094226
             D |   .2979521   .6115311     0.49   0.629    -.9411276    1.537032
               |
c.trust_sd#c.D |  -.0630167   .1263872    -0.50   0.621    -.3191014    .1930681
               |
       firmage |  -.0110074    .001892    -5.82   0.000    -.0148409   -.0071739
      firmage2 |   .0001159   .0000491     2.36   0.024     .0000164    .0002154
        gender |  -.0124502   .0337422    -0.37   0.714    -.0808185     .055918
           age |  -.0013066   .0104545    -0.12   0.901    -.0224893    .0198762
          age2 |  -5.71e-06   .0000854    -0.07   0.947    -.0001787    .0001672
        yrinco |   .0041069   .0006488     6.33   0.000     .0027924    .0054214
               |
     education |
            2  |   .0434882   .0489096     0.89   0.380    -.0556121    .1425885
            3  |   .0601535   .0340231     1.77   0.085     -.008784    .1290909
            4  |   .0851727   .0426696     2.00   0.053    -.0012841    .1716296
               |
         _cons |   .8121786   .3046933     2.67   0.011     .1948113    1.429546
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "R\&D exp"

added macro:
               e(Dvar) : "R\&D exp"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col4, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. global ceo = "gender age age2 i.education"

. replace D = above3yrinco
(44,670 real changes made)

. eststo col5: /// more than 3 years in firm
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  11,     37) =      20.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9013
                                                  Adj R-squared   =     0.8874
                                                  Within R-sq.    =     0.0013
Number of clusters (mainethcode) =         38     Root MSE        =     0.5429

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0760444   .0279047     2.73   0.010      .019504    .1325848
             D |   .1402259   .1907154     0.74   0.467    -.2462002     .526652
               |
c.trust_sd#c.D |  -.0235224   .0371268    -0.63   0.530    -.0987484    .0517036
               |
       firmage |  -.0089489   .0016682    -5.36   0.000     -.012329   -.0055688
      firmage2 |   .0000994   .0000451     2.20   0.034     7.96e-06    .0001908
        gender |  -.0148585   .0343966    -0.43   0.668    -.0845527    .0548357
           age |  -.0042024   .0102199    -0.41   0.683    -.0249099     .016505
          age2 |   .0000346   .0000835     0.41   0.681    -.0001345    .0002038
               |
     education |
            2  |    .033927   .0478511     0.71   0.483    -.0630285    .1308825
            3  |   .0473525   .0321659     1.47   0.149    -.0178218    .1125269
            4  |   .0760045    .040262     1.89   0.067     -.005574    .1575829
               |
         _cons |   .8021368    .330419     2.43   0.020     .1326443    1.471629
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       ">3 yrs in firm"

added macro:
               e(Dvar) : ">3 yrs in firm"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col5, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. global ceo = "gender age age2 yrinco i.education"

. replace D = firstgen | nonUSUKedu
(43,302 real changes made)

. eststo col6: /// born or educated abroad
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      15.94
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0026
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0588936   .0197989     2.97   0.005     .0187772      .09901
             D |  -.1986203   .3673142    -0.54   0.592    -.9428695     .545629
               |
c.trust_sd#c.D |   .0565868   .0712617     0.79   0.432    -.0878031    .2009768
               |
       firmage |  -.0109566   .0018651    -5.87   0.000    -.0147356   -.0071775
      firmage2 |   .0001161   .0000492     2.36   0.024     .0000164    .0002159
        gender |    -.00997    .033395    -0.30   0.767    -.0776347    .0576947
           age |   -.001197   .0102187    -0.12   0.907    -.0219022    .0195081
          age2 |  -6.83e-06   .0000836    -0.08   0.935    -.0001763    .0001626
        yrinco |    .004086   .0005681     7.19   0.000     .0029349    .0052371
               |
     education |
            2  |    .044987   .0476338     0.94   0.351    -.0515282    .1415022
            3  |   .0599782   .0323444     1.85   0.072    -.0055578    .1255143
            4  |   .0810759   .0423416     1.91   0.063    -.0047164    .1668682
               |
         _cons |   .8247418    .289963     2.84   0.007     .2372209    1.412263
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Born/edu abroad"

added macro:
               e(Dvar) : "Born/edu abroad"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col6, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = firstgen
(4,123 real changes made)

. eststo col7: /// born abroad
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     29,384
Absorbing 2 HDFE groups                           F(  12,     37) =      18.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9014
                                                  Adj R-squared   =     0.8875
                                                  Within R-sq.    =     0.0026
Number of clusters (mainethcode) =         38     Root MSE        =     0.5426

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0563453   .0188047     3.00   0.005     .0182433    .0944473
             D |  -1.035664   .4483461    -2.31   0.027      -1.9441   -.1272288
               |
c.trust_sd#c.D |   .2430073   .0858313     2.83   0.007     .0690965    .4169181
               |
       firmage |  -.0109904   .0019418    -5.66   0.000    -.0149248   -.0070559
      firmage2 |   .0001173   .0000495     2.37   0.023     .0000169    .0002177
        gender |  -.0121233   .0334059    -0.36   0.719    -.0798101    .0555635
           age |  -.0008853   .0102221    -0.09   0.931    -.0215973    .0198267
          age2 |  -.0000105   .0000836    -0.13   0.901    -.0001798    .0001589
        yrinco |    .004132   .0005837     7.08   0.000     .0029494    .0053147
               |
     education |
            2  |   .0456167   .0457926     1.00   0.326    -.0471679    .1384014
            3  |   .0625828   .0311791     2.01   0.052     -.000592    .1257576
            4  |   .0832472   .0402327     2.07   0.046     .0017279    .1647664
               |
         _cons |   .8352572   .2904295     2.88   0.007     .2467912    1.423723
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3598           0        3598     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Born abroad"

added macro:
               e(Dvar) : "Born abroad"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      29384       3598

.                 eststo col7, add(nofirms r(ndistinct))
(e(nofirms) = 3598 added)

. replace D = sameethnames
(10,831 real changes made, 6,909 to missing)

. eststo col8: /// same-ethnicity first name
>         reghdfe ash_f1allpat c.trust_sd##c.D ${firm} ${ceo} ///
>         if ${sample}, a(boardid year) cluster(${cluster}) keepsin
WARNING: Singleton observations not dropped; statistical significance is biased (link)
(MWFE estimator converged in 7 iterations)

HDFE Linear regression                            Number of obs   =     28,035
Absorbing 2 HDFE groups                           F(  12,     37) =      98.06
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9037
                                                  Adj R-squared   =     0.8899
                                                  Within R-sq.    =     0.0021
Number of clusters (mainethcode) =         38     Root MSE        =     0.5404

                             (Std. err. adjusted for 38 clusters in mainethcode)
--------------------------------------------------------------------------------
               |               Robust
  ash_f1allpat | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------+----------------------------------------------------------------
      trust_sd |   .0580007   .0179005     3.24   0.003     .0217309    .0942705
             D |  -.3857387   .2826082    -1.36   0.181    -.9583573    .1868799
               |
c.trust_sd#c.D |   .0854677   .0523504     1.63   0.111    -.0206043    .1915397
               |
       firmage |  -.0095657   .0015761    -6.07   0.000    -.0127591   -.0063723
      firmage2 |   .0000926   .0000454     2.04   0.048     7.15e-07    .0001845
        gender |  -.0247958     .04116    -0.60   0.551     -.108194    .0586023
           age |  -.0051534   .0108498    -0.47   0.638    -.0271371    .0168303
          age2 |   .0000284   .0000893     0.32   0.752    -.0001524    .0002093
        yrinco |   .0036582   .0006244     5.86   0.000     .0023931    .0049234
               |
     education |
            2  |   .0284186   .0510076     0.56   0.581    -.0749327    .1317699
            3  |   .0338993   .0356944     0.95   0.348    -.0384245     .106223
            4  |    .063694   .0462486     1.38   0.177    -.0300146    .1574026
               |
         _cons |   .9747945   .3228819     3.02   0.005     .3205735    1.629015
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     boardid |      3495           0        3495     |
        year |        12           1          11     |
-----------------------------------------------------+

.                 estadd local Dvar       "Same-eth names"

added macro:
               e(Dvar) : "Same-eth names"

.                 estadd local FE         "X"

added macro:
                 e(FE) : "X"

.                 estadd local controls   "X"

added macro:
           e(controls) : "X"

.                 distinct boardid if e(sample)

         |        Observations
         |      total   distinct
---------+----------------------
 boardid |      28035       3495

.                 eststo col8, add(nofirms r(ndistinct))
(e(nofirms) = 3495 added)

. 
. esttab /*using "Table A12_Effect by background and experience_Difference.tex"*/, ///
>         cells(b(star fmt(3)) se(par fmt(3))) starlevels(* 0.1 ** 0.05 *** 0.01) ///
>         nomtitle collabels(none) label varwidth(23) modelwidth(13) ///
>         mgroups("arsinh(Future patent applications)", pattern(1 0 0 0 0 0 0 0) ///
>                 prefix(\multicolumn{@span}{c}{) suffix(}) span) ///
>         keep(c.trust_sd#c.D) order(c.trust_sd#c.D) coeflab(c.trust_sd#c.D "Difference: B - A") ///
>         stats(Dvar FE controls N nofirms, fmt(%9.0fc %9.0fc) ///
>                 labels("CEO's background" "Firm \& Year FEs" "Baseline controls" "Observations" "Firms"))

---------------------------------------------------------------------------------------------------------------------------------------------------------------
                        \multicolumn{8}{c}{arsinh(Future patent applications)}                                                                                 
                                  (1)              (2)              (3)              (4)              (5)              (6)              (7)              (8)   
---------------------------------------------------------------------------------------------------------------------------------------------------------------
Difference: B - A              -0.023           -0.064           -0.102**         -0.063           -0.024            0.057            0.243***         0.085   
                              (0.029)          (0.060)          (0.047)          (0.126)          (0.037)          (0.071)          (0.086)          (0.052)   
---------------------------------------------------------------------------------------------------------------------------------------------------------------
CEO's background             Graduate        Doctorate     Non-MBA grad         R\&D exp    >3 yrs in firm    Born/edu abroad      Born abroad    Same-eth names   
Firm \& Year FEs                    X                X                X                X                X                X                X                X   
Baseline controls                   X                X                X                X                X                X                X                X   
Observations                   29,384           29,384           29,384           29,384           29,384           29,384           29,384           28,035   
Firms                           3,598            3,598            3,598            3,598            3,598            3,598            3,598            3,495   
---------------------------------------------------------------------------------------------------------------------------------------------------------------

. 
. cap log close
